Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder.

Background: Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive models for BD based on data from brain imaging are expanding but have often been limited using only a single modality and the exclusion of the cerebellum, which may be relevant in BD.

Failure to breathe persists without air hunger or alarm following amygdala seizures.

Postictal apnea is thought to be a major cause of sudden unexpected death in epilepsy (SUDEP). However, the mechanisms underlying postictal apnea are unknown. To understand causes of postictal apnea, we used a multimodal approach to study brain mechanisms of breathing control in 20 patients (ranging from pediatric to adult) undergoing intracranial electroencephalography for intractable epilepsy.

Cerebellar morphological differences and associations with extrinsic factors in bipolar disorder type I.

Background: The neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Literature suggests differences in cerebellar activity and metabolism in BD, however findings on structural differences remain contradictory.

Functional connectivity of the cerebellar vermis in bipolar disorder and associations with mood.

Purpose: Studies of the neural underpinnings of bipolar type I disorder have focused on the emotional control network. However, there is also growing evidence for cerebellar involvement, including abnormal structure, function, and metabolism. Here, we sought to assess functional connectivity of the cerebellar vermis with the cerebrum in bipolar disorder and to assess whether connectivity might depend on mood.

Functional Connectivity of the Cerebellar Vermis in Bipolar Disorder and Associations with Mood.

Purpose: Studies of the neural underpinnings of bipolar type I disorder have focused on the emotional control network. However, there is also growing evidence for cerebellar involvement, including abnormal structure, function, and metabolism. Here, we sought to assess functional connectivity of the cerebellum with the cerebrum in bipolar disorder and to assess whether any effects might depend on mood.

Intoxicating effects of alcohol depend on acid-sensing ion channels.

Persons at risk for developing alcohol use disorder (AUD) differ in their sensitivity to acute alcohol intoxication. Alcohol effects are complex and thought to depend on multiple mechanisms. Here, we explored whether acid-sensing ion channels (ASICs) might play a role.

Metabolic abnormalities in the basal ganglia and cerebellum in bipolar disorder: A multi-modal MR study.

Aims: Bipolar type I disorder (BD) is characterized by severe mood swings and occurs in about 1% of the population. The mechanisms underlying the disorder remain unknown. Prior studies have suggested abnormalities in brain metabolism using H and P magnetic resonance spectroscopy (MRS).

A human amygdala site that inhibits respiration and elicits apnea in pediatric epilepsy.

BACKGROUNDSeizure-induced inhibition of respiration plays a critical role in sudden unexpected death in epilepsy (SUDEP). However, the mechanisms underlying seizure-induced central apnea in pediatric epilepsy are unknown.METHODSWe studied 8 pediatric patients with intractable epilepsy undergoing intracranial electroencephalography.